Evaluation of respiratory and cardiac motion correction schemes in dual gated PET/CT cardiac imaging.

F. Lamare, A. Le Maitre, M. Dawood, K. P. Schäfers, P. Fernandez, O. E. Rimoldi, D. Visvikis
Med. Phys.. 2014-06-12; 41(7): 072504
DOI: 10.1118/1.4881099

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1. Med Phys. 2014 Jul;41(7):072504. doi: 10.1118/1.4881099.

Evaluation of respiratory and cardiac motion correction schemes in dual gated
PET/CT cardiac imaging.

Lamare F(1), Le Maitre A(2), Dawood M(3), Schäfers KP(3), Fernandez P(1), Rimoldi
OE(4), Visvikis D(2).

Author information:
(1)Univ. Bordeaux, INCIA, UMR 5287, F-33400 Talence, France; CNRS, INCIA, UMR
5287, F-33400 Talence, France; and Service de Médecine Nucléaire, Hôpital
Pellegrin, CHU de Bordeaux, 33076 Bordeaux, France.
(2)INSERM, UMR1101, LaTIM, Université de Bretagne Occidentale, 29609 Brest,
(3)European Institute for Molecular Imaging, University of Münster, Mendelstr.
11, 48149 Münster, Germany.
(4)Vita-Salute University and Scientific Institute San Raffaele, Milan, Italy and
CNR Istituto di Bioimmagini e Fisiologia Molecolare, Milan, Italy.

PURPOSE: Cardiac imaging suffers from both respiratory and cardiac motion. One of
the proposed solutions involves double gated acquisitions. Although such an
approach may lead to both respiratory and cardiac motion compensation there are
issues associated with (a) the combination of data from cardiac and respiratory
motion bins, and (b) poor statistical quality images as a result of using only
part of the acquired data. The main objective of this work was to evaluate
different schemes of combining binned data in order to identify the best strategy
to reconstruct motion free cardiac images from dual gated positron emission
tomography (PET) acquisitions.
METHODS: A digital phantom study as well as seven human studies were used in this
evaluation. PET data were acquired in list mode (LM). A real-time position
management system and an electrocardiogram device were used to provide the
respiratory and cardiac motion triggers registered within the LM file. Acquired
data were subsequently binned considering four and six cardiac gates, or the
diastole only in combination with eight respiratory amplitude gates. PET images
were corrected for attenuation, but no randoms nor scatter corrections were
included. Reconstructed images from each of the bins considered above were
subsequently used in combination with an affine or an elastic registration
algorithm to derive transformation parameters allowing the combination of all
acquired data in a particular position in the cardiac and respiratory cycles.
Images were assessed in terms of signal-to-noise ratio (SNR), contrast, image
profile, coefficient-of-variation (COV), and relative difference of the recovered
activity concentration.
RESULTS: Regardless of the considered motion compensation strategy, the nonrigid
motion model performed better than the affine model, leading to higher SNR and
contrast combined with a lower COV. Nevertheless, when compensating for
respiration only, no statistically significant differences were observed in the
performance of the two motion models considered. Superior image SNR and contrast
were seen using the affine respiratory motion model in combination with the
diastole cardiac bin in comparison to the use of the whole cardiac cycle. In
contrast, when simultaneously correcting for cardiac beating and respiration, the
elastic respiratory motion model outperformed the affine model. In this context,
four cardiac bins associated with eight respiratory amplitude bins seemed to be
CONCLUSIONS: Considering the compensation of respiratory motion effects only,
both affine and elastic based approaches led to an accurate resizing and
positioning of the myocardium. The use of the diastolic phase combined with an
affine model based respiratory motion correction may therefore be a simple
approach leading to significant quality improvements in cardiac PET imaging.
However, the best performance was obtained with the combined correction for both
cardiac and respiratory movements considering all the dual-gated bins
independently through the use of an elastic model based motion compensation.

DOI: 10.1118/1.4881099
PMID: 24989407 [Indexed for MEDLINE]

Auteurs Bordeaux Neurocampus